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What are the Conditions of Riparian Ecosystems? Identifying Impaired Floodplain Ecosystems across the Western U.S. Using the Riparian Condition Assessment (RCA) Tool

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Environmental stressors associated with human land and water-use activities have degraded many riparian ecosystems across the western United States. These stressors include (i) the widespread expansion of invasive plant species that displace native vegetation and exacerbate streamflow and sediment regime alteration; (ii) agricultural and urban development in valley bottoms that decouple streams and rivers from their floodplains and reduce instream wood recruitment and retention; and (iii) flow modification that reduces water quantity and quality, degrading aquatic habitats. Here we apply a novel drainage network model to assess the impacts of multiple stressors on reach-scale riparian condition across two large U.S. regions. In this application, we performed a riparian condition assessment evaluating three dominant stressors: (1) riparian vegetation departure from historical condition; (2) land-use intensity within valley bottoms; and (3) floodplain fragmentation caused by infrastructure within valley bottoms, combining these stressors in a fuzzy inference system. We used freely available, geospatial data to estimate reach-scale (500 m) riparian condition for 52,800 km of perennial streams and rivers, 25,600 km in Utah, and 27,200 km in 12 watersheds of the interior Columbia River Basin (CRB). Model outputs showed that riparian condition has been at least moderately impaired across ≈70% of the streams and rivers in Utah and ≈49% in the CRB. We found 84% agreement (Cohen’s ĸ = 0.79) between modeled reaches and field plots, indicating that modeled riparian condition reasonably approximates on-the-ground conditions. Our approach to assessing riparian condition can be used to prioritize watershed-scale floodplain conservation and restoration by providing network-scale data on the extent and severity of riparian degradation. The approach that we applied here is flexible and can be expanded to run with additional riparian stressor data and/or finer resolution input data.
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Environmental Management
https://doi.org/10.1007/s00267-018-1061-2
What are the Conditions of Riparian Ecosystems? Identifying
Impaired Floodplain Ecosystems across the Western U.S. Using the
Riparian Condition Assessment (RCA) Tool
William W. Macfarlane 1Jordan T. Gilbert1Joshua D. Gilbert1William C. Saunders1,2 Nate Hough-Snee3
Chalese Hafen1Joseph M. Wheaton1,4 Stephen N. Bennett1,2,4
Received: 17 November 2017 / Accepted: 25 April 2018
© Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract
Environmental stressors associated with human land and water-use activities have degraded many riparian ecosystems across
the western United States. These stressors include (i) the widespread expansion of invasive plant species that displace native
vegetation and exacerbate streamow and sediment regime alteration; (ii) agricultural and urban development in valley
bottoms that decouple streams and rivers from their oodplains and reduce instream wood recruitment and retention; and (iii)
ow modication that reduces water quantity and quality, degrading aquatic habitats. Here we apply a novel drainage
network model to assess the impacts of multiple stressors on reach-scale riparian condition across two large U.S. regions. In
this application, we performed a riparian condition assessment evaluating three dominant stressors: (1) riparian vegetation
departure from historical condition; (2) land-use intensity within valley bottoms; and (3) oodplain fragmentation caused by
infrastructure within valley bottoms, combining these stressors in a fuzzy inference system. We used freely available,
geospatial data to estimate reach-scale (500 m) riparian condition for 52,800 km of perennial streams and rivers, 25,600 km
in Utah, and 27,200 km in 12 watersheds of the interior Columbia River Basin (CRB). Model outputs showed that riparian
condition has been at least moderately impaired across 70% of the streams and rivers in Utah and 49% in the CRB. We
found 84% agreement (Cohensĸ=0.79) between modeled reaches and eld plots, indicating that modeled riparian
condition reasonably approximates on-the-ground conditions. Our approach to assessing riparian condition can be used to
prioritize watershed-scale oodplain conservation and restoration by providing network-scale data on the extent and severity
of riparian degradation. The approach that we applied here is exible and can be expanded to run with additional riparian
stressor data and/or ner resolution input data.
Keywords Conservation planning Riparian restoration Watershed condition assessment Riparian degradation
Floodplain ecology Columbia River Basin Utah
Introduction
Floodplain riparian ecosystems form the ecotone between
streams and rivers and the terrestrial landscapes they con-
nect, providing important ecosystem services for humans
(Castellarin et al. 2011; DeLaney 1995; Lowrance et al.
1997; Mander et al. 2005) and vital habitat for numerous
plant and animal species (Baron et al. 2003; Naiman and
and Decamps 1997; Naiman et al. 2000). Although ood-
plain riparian ecosystems (herein oodplain ecosystems)
represent a small portion of earths surface area, they pro-
vide a disproportionately large amount of ecosystem ser-
vices (Costanza et al. 2016; Tockner and Stanford 2002).
Intact oodplains and robust riparian vegetation attenuate
*William W. Macfarlane
wally.macfarlane@usu.edu
1Department of Watershed Sciences, Utah State University, 5210
Old Main Hill, Logan, UT 84322-5210, USA
2Eco Logical Research, Inc., Providence, UT 84332, USA
3Meadow Run Environmental, LLC, Leavenworth, WA 98826,
USA
4Anabranch Solutions, LLC, Newton, UT 84327, USA
Electronic supplementary material The online version of this article
(https://doi.org/10.1007/s00267-018-1061-2) contains supplementary
material, which is available to authorized users.
1234567890();,:
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oods (Tabacchi et al. 2000; Woltemade and Potter 1994),
and play vital roles in cycling nutrients and organic matter
from adjacent landscapes (Lowrance 1998), improving
downstream water quality. In addition to buffering streams
and rivers, oodplain ecosystems also provide recreational
opportunities and essential land use functions (DeFries et al.
2004; Gren et al. 1995). Similarly, these ecosystems support
especially high biodiversity (Tockner and Stanford 2002;
Ward et al. 1999) and are critically important for many
wildlife species that are of great conservation concern
(Golet et al. 2008; Kus 1998) or high cultural or economic
value (Jeffres et al. 2008). However, despite their impor-
tance, riparian ecosystems, and the streams and rivers that
traverse them are among the worlds most heavily degraded
landscapes (Dudgeon et al. 2006; Opperman et al. 2009).
Habitat degradation and biological invasions are the two
leading causes of ecosystem alteration and biodiversity loss
worldwide (Fahrig 2003; Pimentel et al. 2000; Vitousek
et al. 1997), and these stressorsimpacts are particularly
evident in oodplain ecosystems (Shafroth et al. 2002;
Stohlgren et al. 1998; Tockner and Stanford 2002).
Removal of native riparian vegetation, replacement of
oodplain habitats with impervious surfaces, and alteration
of oodplain topography by transportation infrastructure
(Blanton and Marcus 2013; Hall et al. 2007) alter surface
water drainage patterns (May et al. 1999) and hydrologic
regimes (Booth and Jackson 1997). These hydrologic
impacts subsequently alter stream channel geometry
(Taniguchi and Biggs 2015) and water chemistry (Carpenter
et al. 1998; Liess and Schulz 1999; Schoonover et al. 2005).
Riparian forest clearing for agriculture also reduces stream
shading (Allan 2004; Klemas 2014), increases stream tem-
perature (Beschta and Taylor 1988), and removes riparian
sources of large woody debris (Gurnell et al. 1995).
In the western U.S., non-native riparian vegetation, like
tamarisk (Tamarix spp.) and Russian olive (Elaeagnus spp.
e.g., Shafroth et al. 2002; Stromberg et al. 2007), further
alters riparian habitat structure, terrestrialaquatic linkages
(Roon et al. 2014,2016), and aquatic communities (Stella
et al. 2013). Additionally, habitat degradation and biologi-
cal invasions occur in tandem with larger, global phenom-
ena like climate-induced changes to rainfall, runoff, and
streamow (Galloway et al. 2004; Ormerod et al. 2010; Poff
et al. 2002). Moreover, biocontrol efforts undertaken to
control invasive woody vegetation can have unforeseen
consequences. For example, since the tamarisk beetle
(Diorhaba spp.) was released in 2001, it has caused wide-
spread tamarisk defoliation and decline throughout the
Colorado River Basin (Bloodworth et al. 2016). This
reduction in tamarisk cover has helped restore habitat for
some native shrub and tree species. However, where
tamarisk has declined and hydrology has remained altered,
limited woody vegetation has replaced tamarisk, reducing
habitat abundance for wildlife species who rely on tamarisk
for habitat (Bloodworth et al. 2016). Nevertheless, the
cumulative effects of biotic and anthropogenic impacts have
resulted in signicantly different riparian and instream
habitats than those in which many native sh and riparian
fauna evolved (May et al. 1999). These alterations reduce
native species abundance and diversity (Rolls and
Arthington 2014; Royan et al. 2015) and decouple impor-
tant linkages between biological communities and their
habitats (Foley et al. 2005; Hooper et al. 2005).
Floodplain degradation associated with riparian vegeta-
tion change (Macfarlane et al. 2016a), intensive land use
(Allan 2004), and transportation infrastructure (Blanton and
Marcus 2013; Forman et al. 2002) is common across wes-
tern North America, yet regional assessments of how these
stressors align to adversely impact reach-scale riparian
condition are rare. We attribute this to several factors: (1)
methodological limitations of combining multiple stressors
at the regional scale (Goetz 2006); (2) lack of condence in
using nationally available land cover data to assess riparian
condition (Johansen and Phinn 2006); and (3) the cost
prohibitive nature of using high-resolution imagery at large
spatial scales (Salo et al. 2016).
Consequently, riparian ecosystem degradation studies
often examine only small landscapes or isolated causes of
degradation (e.g. Hough-Snee et al. 2013). This lack of
comprehensive riparian condition data challenges resource
managers tasked with restoring large oodplain ecosystems,
often entire watersheds, leaving them with only locally
available data on how and where multiple stressors have
impacted these ecosystems.
In an effort to improve river and riparian management,
valley bottom mapping (Gilbert et al. 2016) and reach scale
vegetation change inventories have been produced for all
perennial streamsvalley bottoms within the state of Utah
and across several interior Columbia River Basin (CRB)
watersheds (Macfarlane et al. 2016a). While Macfarlane
et al. (2016a) cataloged the extent to which valley bottoms
have been impacted by non-native vegetation and upland
encroachment, their analysis did not directly account for the
impacts of land-use intensity and oodplain fragmentation
on riparian ecosystems. Given the importance of functional
riparian ecosystems to sh and wildlife populations, the
enormous extent of riparian degradation across the western
U.S. (Kauffman et al. 1997), and a general lack of riparian
condition information in many regions, riparian assessments
that account for these additional stressors are increasingly
important for sustainable watershed management.
We developed a spatially explicit framework for asses-
sing riparian condition that can be used for reach-level
conservation and restoration planning across broad geo-
graphic areas (Harris and Olson 1997). Our objectives were
to (1) develop a generic model that can use either relatively
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coarse or high-resolution land cover, transportation infra-
structure, and land-use data to assess riparian condition, and
(2) demonstrate the models utility in a western U.S. con-
text, applying the model using relatively coarse, nationally
available data to assess riparian condition across a large
range of physiographic settings in both the state of Utah and
the CRB, USA.
Methods
Study Locations
We focused the riparian condition assessment (RCA) tool
on perennial streams across Utah (25,600 km), and within
12 CRB watersheds that are of sheries management and
restoration concern (Fig. 1). Watersheds within the CRB
included the John Day and Upper Grande Ronde in Oregon,
the Tucannon, Entiat, Wenatchee, and Asotin in Washing-
ton, and the Upper Salmon, Yankee Fork, Lemhi, Lochsa,
Lower Clearwater, and South Fork Clearwater in Idaho
(totaling 27,200 km of streams). These watersheds occur in
the Columbia Plateau Physiographic Province (Vigil et al.
2000) which includes a diverse range of mountains, pla-
teaus, canyons, and rolling hills (Fig. 1). The CRB effort
was part of the Columbia Habitat Monitoring Program
(CHaMP; http://champmonitoring.org) which tracks the
status and trend of anadromous salmonid habitat throughout
the CRB (Bouwes et al. 2011).
Utah is a physiographically diverse landscape covering
219,808 km2that range from alpine meadows to desert
canyons, with riparian conditions varying widely based on
physical setting and management history. The state of Utah
includes three primary physiographic regions, each with
unique topographic, geologic, and geomorphic character-
istics: the Colorado Plateau, the Basin and Range, and the
Middle Rocky Mountains (Vigil et al. 2000). Utahs ele-
vation ranges from 664 m at Beaver Dam Wash in south-
western Utah to 4123 m on Kings Peak in the Uinta
Mountains. Utah provided an ideal range of landscapes
across which we could test the robustness of an RCA
approach.
Differentiating Valley Bottom Setting
By denition, a valley bottom is composed of active and
inactive stream channels and their oodplains (Fryirs et al.
2016; Wheaton et al. 2015). Fryirs and Brierley (2013) used
the position of the channel on the valley bottom oor to
dene ranges of connement that differentiate valley bot-
tom settings. This includes conned, partly conned and
laterally unconned. Differentiation of these valley bottom
settings reects the position of the channel relative to the
valley bottom margin, indicating how often and over what
distance the channel impinges on that margin. In our clas-
sication, a conned valley settings is where the channel
abuts a conning margin greater than 85% of its length, a
partly conned valley setting is where the channel abuts a
conning margin 1085% of its length, and a laterally
unconned valley setting is where the channel abuts a
conning margin less than 10% of its length.
In our RCA we treated streams with conned valley
bottom settings differently than streams with partly conned
and unconned valley bottom settings (hereafter both
referred to as unconned) because conned streams lack a
oodplain (Wheaton et al. 2015), have limited space to
grow riparian vegetation, and are difcult to detect from
medium-resolution satellite imagery (Macfarlane et al.
2016a). Consequently, conned reaches were assigned to
one of two categories: conned-impacted or conned-
unimpacted. A reach was considered impacted if there was a
detectible reduction in vegetation or conversion of land or
transportation infrastructure within the valley bottom.
To separate conned from unconned streams within the
models automated workow, we used valley bottom width
as a proxy for connement, dening an adjustable valley
bottom-width threshold parameter that represents valley
bottom width in meters (which was calculated automatically
for each reach). To calibrate the valley bottom-width
threshold, we calculated valley bottom connement using
the approach outlined in Fryirs et al. (2016) and the con-
nement tool developed in O'Brien et al. (In Revision). For
each watershed, the total length of conned streams was
calculated using the connement tool. These length values
were used to calibrate the valley bottom-width threshold.
Specically, for each watershed within the study area, the
valley bottom-width threshold was adjusted until the
resulting stream lengths matched the conned streams
lengths as calculated by the connement tool.
Riparian Condition Assessment
The RCA tool identies riparian condition across valley
bottoms. We split valley bottoms into a series of Thiessen
polygons with centroids located at the midpoint of each
500-m stream segment (Fig. 2). Thiessen polygons were
chosen for this process because their geometric properties
guarantee that all points within a polygon are closer to that
polygons centroid than to any other polygon (Esri 2016b).
This ensures that land cover and land use adjacent to the
reach are attributed to the correct stream segment, even
when working with irregular planform geometries and
valley bottoms.
Riparian condition was summarized in the resulting
analysis polygons (Fig. 2) using an algorithm based on lines
of evidence that include: (1) riparian vegetation departure
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(RVD) from historic condition, (2) land-use intensity, and
(3) impediments to oodplain accessibility caused by
transportation infrastructure (e.g., raised grades; Blanton
and Marcus 2013). Each drainage network segment was
attributed with continuous values for each line of evidence.
The lines of evidence were combined using an FIS to
Fig. 1 Study locations within the
state of Utah and 12 interior
Columbia River Basin
watersheds of sheries
management concern. These are
mapped over US Environmental
Protection Agency Level III
Ecoregions for additional
context
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Fig. 2 Conceptual diagram of riparian condition assessment (RCA)
tool showing how midpoints of a drainage network (a) are used to
generate Thiessen polygons (b). Riparian vegetation departure index
outputs (c) are combined with land-use intensity (d) and oodplain
accessibility outputs (e) within a Fuzzy Inference System (f) to pro-
duce a segmented drainage network containing riparian condition
assessment scores (g)
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collectively estimate riparian condition based on a linguis-
tic, expert-based rule system (Fig. 2).
RVD Index
To assess riparian vegetation condition, we used the RVD
index (Macfarlane et al. 2016a). The RVD index calculates
riparian vegetations departure from its historic condition as
the ratio of current vegetation cover to estimated historic
riparian vegetation cover. Both existing and historic vege-
tation that occurred as native riparian vegetation were coded
as 1while invasive and upland classes were coded as 0.
For each polygon, the mean vegetation value was calculated
which represents the proportion of native riparian cover
within each polygon. The area of native riparian cells,
within the analysis polygons, modeled in the historic
vegetation input was used as the denominator in the RVD
ratio, and the area of native riparian cells modeled in the
existing vegetation input was used as the numerator. Low
values (closer to 0) signify larger departures from historic
riparian vegetation condition whereas high values (closer to
1) signify small departures.
Assessment of Land-Use Intensity
We classied land-use intensity along a continuum from
zero to one where one is highly altered and zero is unaltered
using 2012 LANDFIRE EVT data (Table S1). Urbaniza-
tion, a land use that often dramatically and permanently
alters riparian ecosystems by covering oodplains with
impervious surfaces, corresponds to a land-use intensity
score of one (highly altered). Agriculture, which modies
oodplain vegetation and disturbance regimes, corresponds
to a land-use intensity score of 0.33 to 0.66, depending on
the intensity (0.33 for pastoral use; 0.66 for row crop).
Areas that have no dened land-use were scored as zero
(unaltered). To attribute input network segments with a
land-use intensity value, we calculated the mean of land-use
intensity values for all cells within each analysis polygon,
resulting in a continuous value between zero and one that
was attributed to the corresponding drainage network
segment.
Assessment of Floodplain Accessibility
The RCA tool is designed to characterize oodplain
accessibility similar to Blanton and Marcus (2013), using a
transportation network layer that includes roads and rail-
roads as line features. We overlaid the transportation net-
work on the valley bottom polygon and split the polygon at
each location where a road or railroad occurred. These splits
separated the valley bottom into portions where the river
has the potential to inundate the oodplain at ood stages
and portions where the rivers access to the oodplain has
been eliminated or severely reduced by elevated railroad
and road grades. It is possible to extend the inputs for this
analysis with other infrastructure like levees, but we
excluded these from our analysis due to lack of nationally
consistent data. We generated the oodplain accessibility
analysis automatically using a geoprocessing method and
visually inspected results to ensure that all disconnected
areas were identied. We made additional manual splits
where lateral connectivity was misclassied by automated
geospatial analyses (Figure S2). For each analysis polygon,
we calculated the proportion of oodplain that is accessible
by the river channel as a ratio from zero (completely dis-
connected) to one (completely connected), and the corre-
sponding drainage network segment was attributed with that
value. The specic geoprocessing steps are described in
Appendix A.
Fuzzy Inference Systems to Score Riparian Condition
We used an FIS to combine the three lines of evidence to
estimate riparian condition over our study areasdrainage
networks (Fig. 3). The FIS provided a consistent and
repeatable framework for combining continuous variable
inputs to produce a continuous output. Categorical ambi-
guity and uncertainty among categories were explicitly
accounted for using fuzzy logic and by representing all
inputs and outputs as continuous variables with overlapping
membership functions for each category (Openshaw 1996;
Zadeh 1996). The FIS also allowed for computing with
words,whereby the three lines of evidence were mathe-
matically combined based on an expert-based rule system
(Table 1) using continuous numeric inputs that provided
continuous numeric outputs (Adriaenssens et al. 2003; Klir
and Yuan 1995). The FIS framework is also exible and
expandable and can easily accommodate additional lines of
evidence for evaluating oodplain condition if such data are
available.
Within the FIS RVD, land-use intensity, and oodplain
accessibility scores were divided into categories. RVD
scores were split into four categories: large, signicant,
minor, and negligible departure, under the framework of
(Macfarlane et al. 2016a). Both land-use intensity and
oodplain accessibility scores were split into three cate-
gories: low, moderate, and high. For each combination of
input category scores, a corresponding rule was created to
determine the output value range and associated categories
(Table 1). The range of output values was split into ve
different categories of riparian condition: very poor, poor,
moderate, good, and intact (Fig. 3). For each input stream
segment, membership in each output category was calcu-
lated, and a nal value attributed to the segment, using the
centroid defuzzication method (Mathworks 2017).
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Case Study Application and Validation
Case study data inputs
Segmented drainage network For our analyses we trim-
med the U.S. Geological Survey (USGS) National Hydro-
graphy Dataset (NHD), a cartographically derived 1:24,000
drainage network (USGS 2016), to perennial streams and
rivers (Table 2). We segmented the resulting perennial
drainage network longitudinally into 500 m long segments.
This was a reasonable length along which to sample 30 m
LANDFIRE land cover and land-use data and oodplain
accessibility. The 500 m reach length used here is also an
ideal resolution for conservation and restoration planning at
large spatial scales (Wheaton et al. 2017).
Valley bottom polygon We used the Valley Bottom
Extraction Tool (V-BET; Gilbert et al. 2016) with addi-
tional manual editing to delineate valley bottoms across the
study areas. V-BET requires three inputs: a digital elevation
model (DEM), a drainage network, and a ow accumulation
raster in which the value for each cell represents the
upstream drainage area (in km2). For this regional applica-
tion, we used USGS National Elevation Data (NED) 10 m
DEMs (Gesch et al. 2009) and NHD 1:24,000 scale dataset
(USGS 2016) as the drainage network. V-BET is based on
the assumptions that: (1) valley bottom width is a function
of upstream drainage area, with wider valley bottoms cor-
responding, crudely, to larger upstream drainage area
(Montgomery 2002; Nardi et al. 2006); (2) the average
slope of a valley bottom is related to upstream drainage
area; the larger the drainage area, the atter the valley
bottom (McNamara et al. 2006; Montgomery 2001;
Schorghofer and Rothman 2002; Tucker and Bras 1998;
Willgoose et al. 1991); and (3) valley bottoms are relatively
at areas with margins often dened by abrupt changes in
slope (Gallant and Dowling 2003).
In our application areas, streams with drainage area of
less than 25 km2were generally conned headwater
streams, those streams with drainage area in the
25250 km2range were in a transition zone where valleys
widened and slopes decreased and those with drainage area
greater than 250 km2were generally larger rivers or
tributaries in alluvial valleys. Following the aforementioned
assumptions, V-BET delineates valley bottoms for these
different types of river reaches distinguished by drainage
area using varying thresholds for valley width and slope.
The larger rivers in alluvial valleys are delineated using
higher maximum valley width and lower slope thresholds,
whereas the valley bottoms of conned headwater reaches
are delineated using narrow maximum width and relatively
higher slope thresholds.
RVD index layer We calculated RVD from historic con-
dition using the RVD index (Macfarlane et al. 2016a). In
this application, Landsat imagery classication of existing
land cover (LANDFIRE EVT; LANDFIRE 2016a) and a
modeled estimate of pre-European settlement land cover
(LANDFIRE BpS; LANDFIRE 2016b) were used to char-
acterize riparian vegetation condition at a given 500 m
reach. LANDFIRE EVT vegetation map units are a mixture
of the following: ecological systems (dened as groups of
vegetative associations that tend to co-occur within
Fig. 3 Fuzzy Inference System for riparian condition assessment
(RCA) tool. This shows the specication of fuzzy membership func-
tions with overlapping values for categorical descriptors in inputs and
outputs
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landscapes with similar ecological processes, substrates,
and environmental gradients(Comer et al. 2003)), aggre-
gations of ecological systems for LANDFIRE purposes
(e.g. riparian systems or sparsely vegetated systems)
(Rollins 2009), and US National Vegetation Classication
alliances (Grossman et al. 1998). For example, the Rocky
Mountain Subalpine-Montane Riparian Shrubland class
consists of montane to subalpine riparian shrublands
occurring as narrow bands of shrubs lining streambanks and
alluvial terraces in narrow to wide, low-gradient valley
bottoms. The dominant shrubs include Alnus incana, Betula
glandulosa, Betula occidentalis, Cornus sericea, Salix
bebbiana, Salix boothii, Salix brachycarpa, Salix drum-
mondiana, Salix eriocephala, Salix geyeriana, Salix mon-
ticola, Salix planifolia, and Salix woli(http://explorer.na
tureserve.org/servlet/NatureServe?searchSystemUid=
ELEMENT_GLOBAL.2.722841). Although used primarily
for wildland re behavior mapping, LANDFIRE map units
were also designed to be useful for applications such as
habitat analysis and sustainable natural resource planning
(Rollins 2009). We chose LANDFIRE data because of the
thorough national coverage, consistent collection methods
and accessible documentation.
Land-use layer We used the 2012 LANDFIRE EVT layer
to derive a land-use intensity layer (see above).
Manually created oodplain connectivity layer Transpor-
tation layers from the TIGER dataset (US Census Bureau
2016) were used to fragment the associated oodplains of
the valley bottoms within our study areas.
Accuracy assessment analysis
A critical component of any geospatial modeling exercise is
a rigorous, ground-based accuracy assessment. Because
RCA outputs are summarized in an ordinal-scale that is
based on a composite score, we chose to validate the
Table 1 Rule table for three
input fuzzy inference system
that models riparian condition
using riparian vegetation
departure, land-use intensity
within the valley bottom, and
oodplain accessibility due to
transportation infrastructure
If Inputs Output
Riparian vegetation
departure
Land-use
intensity
Floodplain
accessibility
Riparian
condition
Rules 1 Large & Low & Low , then Poor
2 Large & Low & Moderate , then Poor
3 Large & Low & High , then Moderate
4 Large & Moderate & Low , then Poor
5 Large & Moderate & High , then Poor
6 Large & High & Low , then Very Poor
7 Signicant & Low & Low , then Moderate
8 Signicant & Low & Moderate , then Moderate
9 Signicant & Low & High , then Good
10 Signicant & Moderate & Low , then Poor
11 Signicant & Moderate & High , then Moderate
12 Signicant & High & Low , then Poor
13 Minor & Low & Low , then Moderate
14 Minor & Low & Moderate , then Good
15 Minor & Low & High , then Intact
16 Minor & Moderate & Low , then Moderate
17 Minor & Moderate & High , then Moderate
18 Minor & High & Low , then Poor
19 Negligible & Low & Low , then Moderate
20 Negligible & Low & Moderate , then Good
21 Negligible & Low & High , then Intact
22 Negligible & Moderate & Low , then Moderate
23 Negligible & Moderate & High , then Good
24 Negligible & High & Low , then Poor
25 Any value & Moderate & Moderate , then Moderate
26 Any value & High & Moderate , then Poor
27 Any value & High & High , then Moderate
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component model inputs (RVD index values, land-use
intensity scores, and oodplain fragmentation percentage)
rather than the composite output scores. We validated our
model using a eld accuracy assessment of: (1) existing
vegetation, (2) land-use type and intensity within the
valley bottom, (3) percentage of oodplain accessible to
the river, and (4) types of transportation infrastructure
present in the valley bottom. We validated RCA inputs in
the Weber River (Utah) and Tucannon River (Washing-
ton) watersheds. We selected validation sites within the
Weber River watershed using a stratied sampling
approach, constrained by public access and quality of
vantage point. In the Tucannon watershed, validation sites
were selected using a systematic survey, stratied by
USEPA Level 4 Ecoregions and whether a polygon
occurred in the mainstem river or tributarystreams.We
conducted systematic, road-based surveys assessing road
access and how well riparian extent and composition
could be assessed from each potential vantage point every
1-km along roadways that traversed rivers and streams of
the watershed.
To validate condition, the framework and rule table of
RCA was used, but with the collected eld data informing
input values rather than the remotely sensed data used in the
analyses. We validated oodplain accessibility and land-use
intensity using eld data to determine input categories. For
example, if eld data showed that the valley bottom was
used as a pasture for livestock grazing, the segment was
attributed with moderate land-use intensity, whereas if there
was no land-use observed in the valley bottom, the segment
was attributed with low land-use intensity. The RVD out-
puts were validated independently (Macfarlane et al.
2016a), and as such modeled RVD values were used in lieu
of eld data. After we attributed every segment with mod-
eled values for RVD and eld values for land-use intensity
and oodplain accessibility, we then applied the rule set
used in the automated model to determine eld data based
riparian condition for each segment. Finally, we directly
compared condition based on eld validation data to con-
dition based on remotely sensed information. Cohen's kappa
statistic (Cohensĸ) was used to measure agreement
between modeled condition and eld-based observations
because it accounts for chance agreement and is more
robust and conservative than an overall error rate (Con-
galton 1991).
Results
Conned Valley Settings
In Utah, nearly half (45%) of the statesperennial drainage
network was classied as conned valley settings (i.e., those
lacking oodplains), consisting predominantly of headwater
streams concentrated in mountainous portions of the state
(Figs. 4and 5and Table 3). Of the conned streams across
the state, 26% (4,104 of 15,539 km) were classied as
impacted vs. 74% (11,436 of 15,539 km) classied as
unimpacted (Table 3). Similarly, the majority (64%) of the
CRB watersheds perennial drainage network was classied
as conned consisting of mostly headwater streams con-
centrated in the mountainous portions of the region (Figs. 6
and 7and Table 4). Of the conned streams across the CRB,
17% (2891 of 17,319 km) were classied as impacted vs.
83% (14,428 of 17,319 km) were classied as unimpacted
(Table 4).
Region-Wide Results
Utah-Wide Application
Across Utah, the RCA tool showed that roughly 70% of
unconned valley bottoms were in moderate to very poor
riparian condition (Fig. 4and Table 5). Floodplains of large
alluvial rivers where agricultural and urban land uses are
common were frequently in poor to very poor condition
(Fig. 4). In contrast, intact and good condition were com-
mon in oodplain ecosystems along large to medium-sized,
rivers in more remote areas of the state such as the Colorado
and Green Rivers, where transportation infrastructure and
intensive land uses are not common. Moderate condition
(41%) oodplains occurred throughout the state, often
corresponding to rural land use common along these river
corridors.
Table 2 Input data used to represent the lines of evidence of riparian condition assessment (RCA) tool
Input data Criteria Source
Riparian Vegetation Departure (RVD) index
output
Riparian vegetation condition http://www.sciencedirect.com/science/article/pii/
S0301479716308489
LANDFIRE 2012 (EVT) Land-use intensity LANDFIRE land cover data http://www.landre.gov/
Roads Transportation infrastructure TIGER https://www.census.gov/geo/maps-data/data/tiger.html
Railroads Transportation infrastructure TIGER https://www.census.gov/geo/maps-data/data/tiger.html
Valley Bottom Extraction Tool (V-BET)
output
Valley bottom delineation http://www.sciencedirect.com/science/article/pii/
S0098300416301935
Environmental Management
Modeled riparian condition was slightly worse in Utahs
western portion, including the Northern Basin and Range/
Wyoming Basin and Central/Mojave Basin and Range
Ecoregions compared to Utahs central (the Wasatch and
Uinta Maintains) and eastern portions (the Colorado Pla-
teaus/Southern Rockies; Fig. 8). The Central/Mojave Basin
and Range Ecoregion, which has experienced widespread
urbanization along the Wasatch Front, exhibited the highest
proportion of very poor condition oodplains (8%; Fig. 8).
The Northern Basin and Range/Wyoming Basin had the
largest percentage of poor condition oodplains (42%),
coinciding with high intensity agriculture. The Wasatch and
Uinta Mountains and Colorado Plateaus/Sothern Rockies
Ecoregions had similar riparian conditions overall, but
degradation in each ecoregion was driven by different fac-
tors. In the Wasatch and Uinta Mountains, agriculture,
roads, and urbanization had the greatest impacts. In con-
trast, in the Colorado Plateau/Southern Rockies, invasive
riparian vegetation had the largest impact on riparian
condition.
Fig. 4 Map showing riparian condition assessment (RCA) tool outputs across the state of Utah
Environmental Management
CRB Watershed Application
Across the 12 CRB watersheds, the RCA model suggests
that just under half (49%) of riparian ecosystems are in
moderate to very poor condition (Fig. 6;Table6). As in
Utah, the RCA tool illustrated spatially variable patterns
of riparian condition within CRB watersheds. Floodplains
in very poor condition were rare (only 1%) and isolated to
only the most developed urban areas (Fig. 6). Poor con-
dition oodplains were uncommon (14%), and were evi-
dent only along large alluvial rivers where agricultural
and urban land uses are common (Fig. 6). Moderate
condition oodplains (34%) were the most widespread
category in the CRB, and were found interspersed
Fig. 5 Pie chart showing riparian condition assessment (RCA) tool outputs for all streams by US Environmental Protection Agency Level III
Ecoregions in Utah
Table 3 Summary of the Utah statewide riparian condition
assessment (RCA) tool for all streams by category
Riparian condition
assessment
Stream length (km) % of drainage
network
Conned-impacted 4103.8 16
Conned-unimpacted 11,436.2 45
Very poor 211.7 1
Poor 2839.4 11
Moderate 4108.4 16
Good 1917.9 7
Intact 1040.6 4
Total 25,658
Environmental Management
throughout the watersheds (Fig. 6). About half (51%) of
the oodplains were found to be either intact (31%)orin
good (20%) condition (Fig. 9and Table 6). Watersheds
with the best condition were the Lochsa, Entiat, and
Yankee Fork (Fig. 9), all relatively remote watersheds that
lack urban and intensive agriculture land use and have
only limited roads. The Lemhi and Tucannon were the
most impacted watersheds (Fig. 9). The Tucannon
watershed is dominated by intensive agriculture, which
has heavily impacted riparian areas. The current riparian
corridor consists primarilyofonlynarrowstreamside
bands of cottonwood (Populus trichocarpa)andalder
(Alnus spp.).
Validation
For ground truthing we surveyed 31 analysis polygons in
the Weber watershed (Figure S4) and 61 analysis polygons
in the Tucannon watershed (Figure S5). Error matrices
were constructed from eld assessments of riparian con-
dition, derived from observations of transportation infra-
structure and land-use intensity. Our model estimates of
condition indicated a high overall level of agreement
between data sources. For all streams we identied an
overall map accuracy of 87% based on the 92 analysis
polygons (Table 7). The calculated Cohensĸwas 0.87.
Using Cohensĸ,one indicates full agreement and zero
indicates complete disagreement between modeled and
measured values. Thus, a 0.87 indicates an almost perfect
agreement (Landis and Koch 1977) between modeled and
eld-based data.
The high accuracy when considering all streams may
result from the simplicity of the binary categorization as
conned-unimpacted or conned-impacted of conned
streams. Therefore, we evaluated the accuracy of polygons
containing only unconned stream segments with ood-
plains (n=71). For this subset, the overall map accuracy
was 84%, and Cohensĸwas 0.79 (Table 8), indicating a
substantialagreement (Landis and Koch 1977). A Cohens
ĸof 0.79 suggests that the RCA tool accurately estimates
riparian condition for medium-sized rivers where the vali-
dation occurred (Weber and Tucannon). However, small
streams with narrow bands of riparian vegetation and small
patches of land use may not have the spatial extent to be
resolved in 30 m datasets. In such settings, the RCA tools
accuracy is likely to be lower.
Fig. 6 Map showing riparian condition assessment (RCA) tool outputs across the select watersheds of the Columbia River Basin
Environmental Management
Fig. 7 Pie chart showing riparian condition assessment (RCA) tool outputs for all streams by select watersheds in the Columbia River Basin
Environmental Management
Discussion
Interpreting and Comparing Riparian Conditions
Between Regions
One should exercise caution when interpreting and com-
paring riparian condition results between Utah and the CRB
watersheds. The CRB watersheds of this study were not
randomly selected and therefore are not an accurate repre-
sentation of the larger CRB. In fact, the selected watersheds
represent some of the least developed portions of the CRB,
skewing the riparian condition assessment to reect more
intact conditions than likely exist elsewhere in the basin. To
emphasize this point, if a Washington statewide analysis
were performed, including watersheds near densely popu-
lated Puget Sound, where many watersheds have been
converted to urban land uses and dense transportation
infrastructures, it is highly likely that the analysis would
have similar overall riparian condition to Utah. Conse-
quently, it is not surprising that 30% of the riparian areas in
Utah were classied as poor or very poor condition com-
pared to only 15% in the watersheds analyzed in the CRB,
which includes no major metropolitan areas, and that only
10% of the riparian areas in Utah compared to 31% in the
CRB were classied as intact.
Land Ownership Implications for Riparian
Management
Riparian management in the western U.S. is complicated by
the fact that most riparian acreage is privately controlled or
intermingled with other ownerships (Leonard et al. 1997).
For instance, while only 21% of the state of Utah is private,
66% of the unconned valley bottoms are privately owned.
Similarly, in the CRB watersheds 41% of the total land is
private while 69% of the unconned valley bottoms are
private (Fig. 10). Because of this disproportionate private
ownership of riparian areas, the involvement and coopera-
tion of private landowners, ranchers, and local, state, and
federal resource managers is critical to the success of
riparian management programs (Leonard et al. 1997).
Moreover, riparian areas under private ownership were
found to be in much poorer condition than publicly admi-
nistered land (Fig. 10). Specically, in Utah 40% of pri-
vately owned riparian areas were in poor condition vs.
publicly administered lands that had only 14% of their
riparian areas in poor condition. In the CRB privately
owned riparian areas were found to have 21% poor vs.
publicly administered land with 4% poor condition. The
higher rates of degradation on private lands underscores the
need to engage with private landowners through agencies
such as the Natural Resources Conservation Service
(NRCS) and state sh and wildlife agencies (e.g. State
Departments of Natural Resources). These agencies can
provide landowners with nancial and technical assistance
to help improve the condition of riparian areas on many
working range, forest, and farmlands.
Uses, Limitations, and Future Work
While higher resolution imagery (e.g., Macfarlane et al.
2016b) and LiDAR (e.g., Johansen et al. 2010) have been
successfully used to drive riparian vegetation classications,
it is often prohibitively expensive to classify large water-
sheds at high resolutions (Salo et al. 2016). Moreover, such
inputs are not uniformly available across many parts of the
U.S. Consequently, our interest was in testing the models
capacity to produce accurate results using nationwide pub-
licly available, moderate resolution datasets. We found that
even when run with these moderate resolution datasets, the
RCA model produced riparian conditions that reasonably
approximated actual conditions, especially in areas where
transportation infrastructure, land-use intensity, and riparian
vegetation conversion are important factors. This nding is
similar to Lisenby and Fryirs (2017) who found that mod-
erate resolution data were appropriate for assessing sedi-
ment connectivity at the watershed scale.
We attribute our successful model outputs using
medium-resolution inputs, at least in part, to processing
Table 4 Summary of riparian condition assessment (RCA) tool
outputs for all streams by category in the Columbia River Basin
watersheds
Riparian condition
assessment
Stream length
(km)
% of drainage
network
Conned-impacted 2891 11
Conned-unimpacted 14,428 53
Very poor 71.5 <1
Poor 1390 5
Moderate 3332 12
Good 1986 7
Intact 3080 11
Total 27,179
Table 5 Summary of Utah statewide riparian condition assessment
(RCA) tool for partly conned and unconned streams by category
Riparian condition
assessment
Stream length
(km)
% of drainage
network
Very poor 211.7 2
Poor 2839.4 28
Moderate 4108.4 41
Good 1917.9 19
Intact 1040.6 10
Total 10,118
Environmental Management
steps within our workow that (1) aggregated land cover
classes into two broad categories (native and non-native/
upland) and (2) averaged condition values over 500 m
reaches. Studies show that classication accuracy greatly
increases when vegetation classes are lumped together (e.g.,
Driese et al. 2004). Nevertheless, the coarseness of the input
data resulted in output data limitations. There are at least
three limitations that are worth discussing: (1) 30 m land
cover classications may be too coarse to consistently
capture narrow riparian areas, (2) 30 m land cover classi-
cations may often misclassify invasive vegetation, and (3)
there is uncertainty in what historic vegetation existed and
at what levels of coverage.
Fig. 8 Pie chart showing riparian condition assessment (RCA) tool outputs for partly conned and unconned streams by US Environmental
Protection Agency Level III Ecoregions in Utah
Table 6 Summary of the riparian condition assessment (RCA) tool
outputs for partly conned and unconned streams by category in the
Columbia River Basin watersheds
Riparian condition
assessment
Stream length
(km)
% of drainage
network
Very poor 71.5 1
Poor 1390.5 14
Moderate 3332 34
Good 1986 20
Intact 3080 31
Total 9860
Environmental Management
In narrow, riparian corridors, 30 m spatial resolution data
appear to be too coarse to adequately capture riparian
condition (e.g., Congalton et al. 2002; Muller 1997).
Further, because riparian areas have steep environmental
gradients that produce many plant species within a short
distance, a given 30 m pixel may contain a mixture of
Fig. 9 Pie chart showing riparian condition assessment (RCA) tool outputs for partly conned and unconned streams by select watersheds in the
Columbia River Basin
Environmental Management
several plant species in various proportions producing
mixed pixels(Zomer et al. 2009). As such, RCA outputs
created using 30 m data are more reliable in wider ood-
plain riparian ecosystems with larger homogeneous patches
of vegetation. In narrower riparian areas, higher resolution
inputs may be more appropriate (e.g., Macfarlane et al.
2016b), or an on-the-ground assessment may be necessary.
Fortunately, with minor modications, the RCA tool can be
run with higher resolution input data. Higher spatial reso-
lution increases the number of pure pixels, thus removing
a large source of error (Zomer et al. 2009), allowing
for ner resolution outputs. Future work will focus
on running the RCA tool with higher resolution inputs
where available.
In the Colorado Plateau ecoregion of Utah, where
tamarisk is the dominant oodplain species (Nagler et al.
2011) land cover classications derived from 30 m data
often fail to capture the full extent of tamarisk invasions.
This is especially true in narrow valley bottoms or gorges
where vegetation can be hard to accurately detect in 30 m
resolution satellite imagery due to shadows. We also attri-
bute this classication failure, at least in part, to large
swaths of tamarisk defoliated by the tamarisk leaf beetles.
The tamarisk beetle was released as a biological control
agent by the U.S. Department of Agriculture and since 2001
tamarisk leaf beetle have defoliated much of tamarisk in this
area (Bloodworth et al. 2016). In the LANDFIREs EVT
classication defoliated tamarisk are often misclassied as
upland classes, likely because these classes have low NDVI
(greenness) values similar to those of defoliated tamarisk
(Macfarlane et al. 2016b). As such, the RCA results indicate
intact and good condition for some of these rivers, yet these
Table 7 Error matrix and Cohens Kappa score for all assessed stream reaches illustrating the agreement of ground based to modeled oodplain
and riparian condition assessment
Field data RCA model output
Impacted Unimpacted Very poor Poor Moderate Good Intact Row total Producer accuracy Omission error
Impacted 11 11 100% 0%
Unimpacted 1 910 90% 10%
Very poor 21 3 67% 33%
Poor 18 2 20 90% 10%
Moderate 21 21 100% 0%
Good 6 12 18 67% 33%
Intact 2 79 78% 22%
Column total 12 9 2 19 29 14 7 92
Consumer accuracy 92% 100% 100% 95% 72% 86% 100%
Commission error 8% 0% 0% 5% 28% 14% 0%
Overall accuracy 87%
Cohensĸ0.87
The diagonal in bold text shows correctly modeled riparian condition
Table 8 Error matrix and
Cohens Kappa score illustrating
the agreement of ground based
to modeled oodplain and
riparian condition assessment
for partly conned and
unconned reaches
Field data RCA model output
Very
poor
Poor Moderate Good Intact Row
total
Producer
accuracy
Omission
error
Very poor 21 3 67% 33%
Poor 18 2 20 90% 10%
Moderate 21 21 100% 0%
Good 6 12 18 67% 33%
Intact 2 79 78% 22%
Column total 2 19 29 14 7 71
Consumer
accuracy
100% 95% 72% 86% 100%
Commission error 0% 5% 28% 14% 0%
Overall accuracy 84%
Cohensĸ0.79
The diagonal in bold text shows correctly modeled riparian condition
Environmental Management
areas are dominated by tamarisk (see for example Colorado
and Green Rivers Fig. 4).
RVD scores, an important input to the RCA tool, depend
on how well the historic vegetation layer captures the his-
toric coverage of native riparian communities. The LAND-
FIRE BpS, which we used in this study, uses a predictive
modeling approach based on plot data and biophysical gra-
dient data layers, but does not incorporate imagery
(LANDFIRE 2016a). As such, historic vegetation data are
inherently coarser than existing vegetation data, which is
based on Landsat satellite imagery (LANDFIRE 2016a).
Despite this, the RCA model outputs still provide a reliable
indicator of riparian modication because the location and
extent of riparian vegetation are highly predictable (i.e.
adjacent to perennial waterways and in oodplains) and the
level of classication needed for model application is rela-
tively coarse (i.e. native vs. non-native riparian vegetation).
Despite precision and accuracy issues associated with
running the RCA tool using medium-resolution inputs, the
RCA tool outputs can be effectively applied to various river
and oodplain restoration and conservation planning
efforts. At the regional scale, RCA outputs can provide
meaningful contextual analyses of riparian condition
between watersheds. By revealing patterns of degradation,
such analyses provide critical information to resources
managers for prioritizing watershed conservation and
restoration efforts (e.g., Corsair et al. 2009). Specically,
RCA outputs can be used to cost effectively identify areas
where restoration may be ineffective owing to high ood-
plain fragmentation (potential sacrice areas), areas in need
of restoration that have the potential to transition toward
improved condition (OBrien et al. 2017), or to prioritize
urban growth management and prevent encroachment on
relatively unimpacted oodplains. Once priority restoration
Fig. 10 Land ownership map showing percent ownership of the entire regions and for partly conned and unconned valley bottoms along with
riparian condition assessment (RCA) tool outputs values by ownership type
Environmental Management
and conservation areas have been identied, targeted col-
lections of higher resolution land cover and land use clas-
sications can be utilized in these priority areas if so
desired. This approach maximizes limited restoration
resources by limiting the collection of costly high-resolution
classications to only where you are likely to get the
greatest return on investment.
Independent of watershed conservation and restoration
planning, RCA outputs can be used for modeling and
evaluating relationships between species that rely on ripar-
ian habitats for portions of their life cycles, and the condi-
tion of those riparian habitats (e.g., Decker et al. 2017). The
RCA tool maps how oodplains have been altered onto
drainage networks. Independently, each vegetation change,
human land use, and transportation infrastructure input used
in the RCA tool directly impacts riparian and aquatic spe-
cies life cycles and community structure. For example,
riparian birds and amphibians, as well as many sh species,
are negatively affected by transportation infrastructure
(Ficetola et al. 2009; Hennings and Edge 2003; Kaufmann
and Hughes 2006; Rieman et al. 1997), non-native riparian
vegetation (Kennedy et al. 2005; Miller et al. 2003), and
riparian land use (Blair 1996; Kauffman and Krueger 1984;
Martin and McIntyre 2007). Additionally, future work
could include pairing predictions of riparian condition with
data on hydrology (e.g., Lane et al. 2017; Wenger et al.
2010), water temperature (e.g., Isaak et al. 2016; McNyset
et al. 2015), and geomorphic setting and context (Beechie
et al. 2013; Kasprak et al. 2016; Wheaton et al. 2015)to
conceptually understand factors that impact biological
communities across river networks.
In this application, our primary intent was to develop a
consistent regional analysis of riparian oodplain condition.
Our selected indicators of riparian oodplain health, RVD,
land use intensity, and oodplain fragmentation were well
suited for this application because they could be con-
sistently mappedusing freely available, region-wide data.
Hydrologic alterations are another important riparian con-
dition stressor. For instance, in the Colorado River basin
water withdrawals from dams and diversions reduce the
magnitude, duration, and frequency of oods, which often
leads to dense thickets of tamarisk along oodplains fol-
lowed by rapid accretion of sediment on oodplains,
resulting in channel narrowing (Dean and Schmidt 2011;
Manners et al. 2014). Yet, hydrologic alteration stressors
were not assessed in this analysis because dam and diver-
sion data are difcult to use and are not regionally con-
sistency and/or available. Nevertheless, this does not
preclude the use of such data in future applications of the
RCA tool because the FIS framework is expandable and can
be modied to include additional inputs when and where
available. In priority watersheds, where funding has allowed
us to collect and analyze a suite of additional stressor data,
we have developed more comprehensive watershed scale
condition assessments (OBrien et al. 2017). We plan to
continue to expand the RCA tool to produce more com-
prehensive riparian condition assessments by including
additional riparian stressors in watersheds where funding
and data are available.
In an effort to examine riparian condition change over
even broader spatial and temporal scales, we plan to run the
RCA tool as a time-varying dynamical model over large
areas such as the entire western U.S. To accomplish this, we
will use Google Earth Engine in a similar fashion to Don-
nelly et al. (2016) and vary vegetation and land use inputs
through time using historic Landsat imagery derivatives. If
the model were to be run in this manner, the outputs might
help measure the effectiveness of restoration actions or
natural ow and climatic variability. Ideally, a time-step
version of the RCA will elucidate informative patterns
associated with urban development, agriculture, vegetation
community shifts due to disturbance (e.g. timber harvest,
re, etc.) and impacts like browse pressure (e.g. from bea-
ver, cattle, elk, etc.).
Conclusions
Effectively managing stream and river ecosystems requires
comprehensive and accurate riparian condition data on how
multiple stressors can affect oodplains. The results of the
newly developed drainage network-based model that we
present here provides one of the rst major riparian con-
ditions assessments across large areas of the interior western
U.S. We found that the watersheds of Utah and the interior
CRB were ideal settings within which to develop and test
our oodplain condition assessment tool due to the diverse
climate, disturbance regimes and land use histories of these
regions. We also found that across our study watersheds,
riparian condition is highly variable, and is often impacted
by a combination of the multiple stressors we examined.
Even when using relatively coarse input data, our con-
dition assessment provides critical information regarding
the extent to which riparian areas remain intact or have been
degraded. As such, these data can enhance river and
oodplain restoration and conservation planning by allow-
ing resource managers to identify the causes of riparian
degradation, prioritize watersheds for conservation, target
areas in need of restoration, and identify areas where
restoration and conservation may be ineffective due to land
use constraints. Although we were able to identify how
land-use intensity, vegetation change, and valley bottom
infrastructure impact oodplains across Utah and the CRB,
spatially explicit, multi-stressor assessments simply do not
exist for much of the world. Fortunately, the framework on
which the model is built provides a foundation for broad
Environmental Management
applications elsewhere in the world where sufcient input
data exist or can be collected. Moreover, the techniques are
scalable to entire regions and/or could be run in smaller
regions with higher resolution inputs.
Data Availability
We generated spatial data layers to enable resource man-
agement agencies, restoration practitioners, and other inter-
ested parties to access and use RCA data to inform their
management decisions. The outputs of this work are publicly
available at: http://rcat.riverscapes.xyz and the source code
of the Riparian Condition Assessment Toolbox (R-CAT) is
available at: https://github.com/Riverscapes/RCAT.
Acknowledgements This work was supported by U.S. Department of
the Interior Bureau of Land Management (USU Award No. 151010),
Utah Department of Natural ResourcesEndangered Species Mitiga-
tion Fund (USU Award No. 140600), Utah Division of Wildlife
ResourcesPittman and Robertson Fund (USU Award No. 150736),
Snake River Salmon Recovery Board through Eco Logical Research
(USU Award No. 200239) and Bonneville Power Administration
(BPA project numbers: CHaMP 2011-006 and ISEMP 2013-017), as
part of the Columbia Habitat Monitoring Program (http://champmo-
nitoring.org) through a sub-award from Eco Logical Research (USU
Award No. 150737). We are grateful to Justin Jimenez (BLM) who
had the vision to undertake a riparian assessment across the Colorado
Plateau, and built the partnerships for successful implementation.
Model development benetted greatly from insights and conversations
with Jeremy Jarnecke (BLM), Russell Norvell (UDWR), Jimi Gragg
(UDWR), Chris Keleher (UDNR), Frank Howe (USU), Justin Shan-
non (UDWR), Gary OBrien (USU), Phaedra Budy (USGS/USU),
Konrad Hafen (USU), Nick Bouwes (USU), Chris Jordan (NOAA),
and the Weber River Watershed Partnership (UT). Adan Banda,
Micael Albonico, Shane Hill, Martha Jensen, Matt Meier, and Chris
Smith provided GIS support. Reid Camp, Andrew Hill, and Scott
Shahverdian provided eld-validation support. We thank two anon-
ymous reviewers and Angus Webb for their review comments that
signicantly improved this paper.
Compliance with Ethical Standards
Conict of interest The authors declare that they have no conict of
interest.
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Environmental Management
... Another method that focuses on remote sensing data rather than more localized field data is the riparian vegetation departure index (RVD; Macfarlane et al. 2018). The RVD index calculates riparian vegetation's departure from its historic condition as the ratio of current vegetation cover to estimated historic riparian vegetation cover (Macfarlane et al. 2017). ...
... The scale goes from "0" (a complete departure from native riparian vegetation) to "1" (the same as historic native riparian vegetation), with numbers near one meaning small differences between historic and current (Macfarlane et al. 2017). Macfarlane et al. (2018) uses this method in several major watersheds in the Columbia Basin (Entiat, Wenatchee, John Day, Upper Grande Ronde, Tucannon, Asotin, Lower Clearwater, South Fork Clearwater, Lochsa, Lemhi, Yankee Fork, and Upper Salmon) to identify at the stream network-scale riparian, floodplain, in-stream, and adjacent land conditions for restoration and conservation purposes. ...
... The RCA tool was developed to assess impacts on riparian condition caused by three dominant stressors: (1) riparian vegetation departure from historical condition, (2) land use intensity within the valley bottom, and (3) floodplain fragmentation due to infrastructure within valley bottoms (Macfarlane et al., 2018). Each stream reach is attributed with continuous values for the three stressors and the condition of each reach is then assessed using a fuzzy inference system. ...
... Beaver Restoration Assessment Tool (BRAT) evaluation of areas with potential risk of beaver dam activity impacting roads, infrastructure or incompatible land uses.APPENDIX 3E: ASSESSING RIPARIAN CONDITIONS TO SUPPORT WOOD ACCUMULATIONThe Riparian Condition Assessment Toolbox (R-CAT; http://rcat.riverscapes.xyz) is a network level assessment tool consisting of the Valley Bottom Extraction Tool (VBET;Gilbert et al., 2016), Riparian Vegetation Departure index (RVD;Macfarlane et al., 2017), and Riparian Condition Assessment tool (RCA;Macfarlane et al., 2018). The questions the tool approximates answers to with remotely sensed data are all questions worth considering:• What is the overall riparian condition? ...
Technical Report
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Chapter 3 of of Low-Tech Process-Based Restoration of Riverscapes: Design Manual (http://lowtechpbr.restoration.usu.edu) Planning for low-tech process-based restoration is similar to planning for other forms of restoration. •We adapt the Conservation Planning Process to show what aspects of the process are distinctive to low-tech process-based restoration. The Conservation Planning Process follows an adaptive management framework and has three phases: i) a Collection and Analysis (focused on planning), ii) a Decision Support (focused on design), and iii) an Application and Evaluation (focused on implementation). •For low-tech restoration, we pose four screening questions to identify where and if low-tech process-based restoration is appropriate. •In the Collection and Analysis Phase, current conditions of the riverscape (valley bottom), constraints and recovery potential are identified to help frame appropriate and realistic treatments and objectives in the design. •Low-tech restoration to reverse structural starvation of riverscapes frequently takes more than one treatment (and design). Therefore, in the design phase we set expectations for how many treatments might be necessaryto achieve the long-term restoration goal of a self-sustaining riverscape. •The implementation of a design involves an iteration between carrying out an individual treatment of structural additions and evaluation. Ultimately, it is assumed project goals will be met if the processes of wood accumulation and/or beaver dam activity make the transition from being mimicked and promoted by treatments to occurring on their own in a self-sustaining fashion. As such, the need for additional treatments versus recognizing the project has achieved its goals is evaluated with respect to the sustainability of these processes.
... Large-scale datasets are generally too coarse for describing the conditions at a specific location within one of our study areas. For example, we often use the Riparian Condition Assessment Tool (RCAT) [53,54], which estimates changes in riparian ecosystems using 30 m LANDFIRE data [55,56]. In some cases, this 30 m resolution is too coarse to accurately capture changes in narrow riparian corridors that are common throughout the Intermountain West. ...
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In 2012, the U.S. Department of Agriculture adopted a new planning rule that outlined a process for developing, amending, and revising land management plans for the 155 National Forests, 20 National Grasslands, and one Tallgrass Prairie managed by the U.S. Forest Service. The rule outlines a framework with three phases: assessment, development/amendment/revision, and monitoring. We are assisting National Forests in the western U.S. with the first phase by completing a series of assessments of riparian and groundwater-dependent ecosystems. Here, we describe our methods and the lessons learned over the course of conducting assessments for seven National Forests. Per the requirements of the planning rule, we conduct a rapid assessment of ecological integrity that uses existing data to evaluate drivers, stressors, structure, function, composition, and connectivity. We have collaborated with National Forests, state agencies, and other research groups to obtain datasets representing various wetland landscape features. Our work supports the plan revision process, from assessment through plan approval, and informs future forest and project planning for the restoration and maintenance of structure, function, composition, and connectivity. We developed our assessment methods in collaboration with resource managers at the National Forest and regional level to ensure useful end products such as published technical reports, literature reviews, photo libraries, or collections of datasets related to riparian and groundwater-dependent ecosystems. Our approach and lessons learned throughout the process are relevant to other resource management planning applications, analyses of landscape condition, as well as assessments of other ecosystems, such as forests or grasslands.
... However, while past research provides some important insights into the roles that vegetation-connectivity linkages may play in regulating geomorphic responses to environmental change, further work is warranted. For instance, in contrast to the wellresearched effects of land use [258][259][260], geomorphic responses to more nuanced and gradual changes in vegetation characteristics, such as those induced by climate variability [261], are much more challenging to identify. In other words, using terminology borrowed from the field of disturbance ecology, the recent focus in biogeomorphology appears to have been primarily on pulse (short-lived) and less on press or ramp (persistent) disturbances [262,263]. ...
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Rivers are complex biophysical systems, constantly adjusting to a suite of changing governing conditions, including vegetation cover within their basins. This review seeks to: (i) highlight the crucial role that vegetation’s influence on the efficiency of clastic material fluxes (geomorphic connectivity) plays in defining mountain fluvial landscape’s behavior; and (ii) identify key challenges which hinder progress in the understanding of this subject. To this end, a selective literature review is carried out to illustrate the pervasiveness of the plants’ effects on geomorphic fluxes within channel networks (longitudinal connectivity), as well as between channels and the broader landscape (lateral connectivity). Taken together, the reviewed evidence lends support to the thesis that vegetation-connectivity linkages play a central role in regulating geomorphic behavior of mountain fluvial systems. The manuscript is concluded by a brief discussion of the need for the integration of mechanistic research into the local feedbacks between plants and sediment fluxes with basin-scale research that considers emergent phenomena.
... The first step to effectively manage riparian areas is knowing the current state and condition of riparian habitats. Rapid assessment methods are a starting point to detect the integrity of riparian areas, assess the degree of deterioration and identify the disturbing agents (Jansen and Robertson, 2001;NRC, 2002;Díaz-Pascacio et al., 2018;Macfarlane et al., 2018). Once the native vegetation's condition has been identified as good, actions for its maintenance and protection should be outlined. ...
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Alterations to flow regimes for water management objectives have degraded river ecosystems worldwide. These alterations are particularly profound in Mediterranean climate regions such as California with strong climatic variability and riverine species highly adapted to the resulting flooding and drought disturbances. However, defining environmental flow targets for Mediterranean rivers is complicated by extreme hydrologic variability and often intensive water management legacies. Improved understanding of the diversity of natural streamflow patterns and their spatial arrangement across Mediterranean regions is needed to support the future development of effective flow targets at appropriate scales for management applications with minimal resource and data requirements. Our study addresses this need through the development of a spatially explicit reach-scale hydrologic classification for California. Dominant hydrologic regimes and their physio-climatic controls are revealed, using available unimpaired and naturalized streamflow time-series and generally available geospatial datasets. This methodology identifies eight natural flow classes representing distinct flow sources, hydrologic characteristics, and catchment controls over rainfall-runoff response. The study provides a broad-scale hydrologic framework upon which flow-ecology relationships could subsequently be established towards reach-scale environmental flows applications in a complex, highly altered Mediterranean region.
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